Nairanjana Dasgupta, Jillian Morrison

Ordinal Data Analysis (eBook, ePUB)

Statistical Perspective with Applications

• Format: ePub

Produktbeschreibung

This book is a step-by-step data story for analysing ordinal data from start to finish. The book is for researchers, statisticians and scientists who are working with data sets where the response is ordinal. This type of data is common in many disciplines, not just in surveys.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 216
• Erscheinungstermin: 4. Juni 2024
• Englisch
• ISBN-13: 9781040030394
• Artikelnr.: 70467997

Autorenporträt

Nairanjana (aka "Jan") Dasgupta is a Regents Professor and Boeing Distinguished Professor of Math and Science Education at Washington State University. She also serves as the Professor of Statistics and Director of the Data Analytics Program. She is a Fellow of ASA and an inductee in the WA State Academy of Sciences. She is passionate about the understandability and applicability of statistical methods in real-life applications.

Jillian Morrison is Assistant Professor of Statistical and Data Sciences at The College of Wooster. She serves as Chair of the Communications Committee and a member of the governing council for the Caucus for Women in Statistics and Data Science. She is also a fellow of the Mathematical Association of America's Project NExT. Her work focuses on applying statistical and data science methods to solve problems in the real world.

Inhaltsangabe

Part 1: Introduction to Ordinal Data 1. Ordinal Data Part 2: Exploratory
Analysis 2. Summarizing Ordinal Data Part 3: Methods for the Analysis of
Ordinal Data 3. Historical Perspective 4. Likert Scale 5. Cumulative
Distribution Function (CDF) Models 6. Latent Variable Models: Structural
Equation Models Part 4: Further Work with Ordinal Data 7. Diagnostics of
the Ordinal Regression Models 8. Simulating Ordinal Models Part 5: Overall
Summary 9. Data Story: Analysis of the Heart Data 10. Tying up Loose Ends
and Overall Summary